CNUR 209 TEST BANK
WITH COMPLETE
QUESTIONS AND
CORRECT DETAILED
ANSWERS (VERIFIED
ANSWERS) 2024-2025
UPDATE
What are inferences? - Answer- - A conclusion or judgment based on evidence
- Judgments are made based on statistical results.
- Statistical inferences must be made cautiously and with great care.
- Decision theory rules were designed to increase the probability that inferences are
accurate.
Descriptive Stats: Degrees of Freedom - Answer- - The number of scores that can vary
is your degree of freedom.
- Generally refers to the number of independent observations in a sample minus the
number of population parameters that must be estimated from sample data.
Parametric - Answer- - Stronger to draw conclusions form because they can
mathematically describe the data that they see (draw more conclusive conclusions from
it)
- interval or ratio level of measurement
- Values of the subject for the variables are normally distributed
- Student t-test, t-test, ANOVA, pearson correlation co-efficient
Non-parametric tests - Answer- - Isn't normal distribution; therefore, it is not
mathematically easily explained (Can't ever draw conclusions like cause and effect)
Measured at nominal and ordinal levels
,- Mann-whitney U test
Compare means between two distinct/independent groups - Answer- Two-sample t-test
(Parametric)
Wilcoxon ranksum test (nonparametric)
Compare two quantitative measurements taken from the same individual - Answer-
Paired t test
Wilcoxon signedrank test
Compare means between three or more distinct/independent groups - Answer- Analysis
of variance (ANOVA)
Kruskal-Wallis test
Estimate the degree of association between two quantitative variables - Answer-
Pearson coefficient of correlation
Spearman's rank correlation
Homegeneity - Answer- Type of reliability testing used with paper and pencil or scales
to address the correlation of each question to the other question within the scale ➢
Looks at the variances
➢ Collect data and the variances between the mean. Those variances around the
mean, when compared with another sample, would be similar.
➢ Should have a middle --> Some people fall above and some fall below
➢ Allows you to generalize it
Outliers - Answer- - Subjects or data points with extreme values that seem unlike the
rest of the sample
Looking for Normal Distribution Violations: - Answer- ➢ Looking at the distribution to
see if it's normal
Shape, skewness, hysteresis
Standard Deviation - Answer- Its symbol is σ
The formula is easy: it is the square root of the Variance.
Variance in this formula is - The average of the squared differences from the Mean.
Statistical Hypothesis: - Answer- statistical inference- Was the intervention being
implemented and di not happen by chance. Ex. Null, direction
One- and Two-sided hypotheses: - Answer- alternative hypothesis
Statistical significance: - Answer- results not random
Hypothesis testing: - Answer- 1. Define the research hypothesis
2. Explain how you are going to operationalize
,3. Set out the null and alternative hypothesis
4. Set the significance level.
5. Make a one- or two-tailed prediction.
6. Determine whether the distribution that you are studying is normal
7. Select an appropriate statistical test
8. Run the statistical tests
9. Reject or fail to reject the null hypothesis.
Type I error - Answer- Null hypothesis is rejected when its true
Type II error - Answer- When the null hypothesis is regarded as true but is in fact false
- often caused by flaws in the research method
Mulitvariate
Bivariate
Univariate - Answer- • Multivariate - Looking at multiple variables and trying to predict
the relationships, and maybe trying to predict if one variable effects another
• Bivariate - Comparing a bit more complex. Comparing different variable being
• Univariate - Simplest form of analysis
Regression Analysis - Answer- Used to predict the value of one variable when the value
of one or more other variables is known
- predict the value of one variable based on the value of one or more variables
- The outcome of analysis is the regression coefficient R.
- The R2 is also called the coefficient of multiple determination.
Reported as R2 = 0.63
What is probability theory? - Answer- - Deductive
- Used to explain or predict
- Expressed as p with values and percentages
Chi-Square Test of Independence - Answer- Tests for differences between expected
frequencies if groups are alike and frequencies actually observed in the data
Ex of how to report results: 2 = 4.98, df = 2, p = 0.05
Analyzing and Reporting Results
Parametric Statistical test Pearson Correlation: - Answer- Tests for the presence of a
relationship between two variables
Analyzing and Reporting Results: Explained Variances - Answer- - Regression Analysis:
The R2 is the variation between two variables expressed as a percentage.
- Cronbach's Alpha Coefficient: Tests internal consistency of measurement scale
Factor Analysis:
- Aids in development of theoretical constructs
- Aids in development of measurement scales
, Factor Analysis: two types - Answer- Confirmatory: know the dimensions
Exploratory: do not have a pre-defined idea of how many dimensions
T-Test: compares two sample means - Answer- - The "One Sample T-Test" or
"Independent Samples T-Test"-compare one group's average value to a single number
- The "paired t-test"-observations in one group is paired with a related observation in the
other group.
Performing Post Hoc Analyses - Answer- Purpose: to determine which groups are
significantly different
without which multivariate hypothesis testing would greatly suffer.
Analysis of Variance (ANOVA) - Answer- Tests for differences between means
More flexible
Multiple versions of ANOVA are available.
Reported as F = 9.75 (2, 95) (p = 0.002)
Post hoc tests are used to determine the location of differences.
Analyzing and Reporting Results: Generalizations - Answer- the application of
information that has been acquired from specific to a general
making careful inferences.
Further Research: stats - Answer- To improve the next study.
Suggestions emerge from the present study.
Strategies to further test framework in use
Conclusions and Implications - QN - Answer- It is different than the conclusion of a
paper
Conclusion is a synthesis of the findings using
Implications differ from conclusions
Judging Statistical Suitability - Answer- Factors that must be considered include:
- Study purpose
- Hypotheses, questions, or objectives
- Design
- Level of measurement
Are there dependent or independent groups?
Was performed appropriately and the results were interpreted correctly?
Was the data for analysis were treated as nominal, ordinal, or interval?
What questions are important when critically appraising statistics in a study? - Answer-
What statistics were used to describe the characteristics of the sample?
Are the data analysis procedures clearly described?
Did statistics address the purpose of the study?
Did the statistics address the objectives, questions, or hypotheses of the study?
Were the statistics appropriate for the level of measurement of each variable?
WITH COMPLETE
QUESTIONS AND
CORRECT DETAILED
ANSWERS (VERIFIED
ANSWERS) 2024-2025
UPDATE
What are inferences? - Answer- - A conclusion or judgment based on evidence
- Judgments are made based on statistical results.
- Statistical inferences must be made cautiously and with great care.
- Decision theory rules were designed to increase the probability that inferences are
accurate.
Descriptive Stats: Degrees of Freedom - Answer- - The number of scores that can vary
is your degree of freedom.
- Generally refers to the number of independent observations in a sample minus the
number of population parameters that must be estimated from sample data.
Parametric - Answer- - Stronger to draw conclusions form because they can
mathematically describe the data that they see (draw more conclusive conclusions from
it)
- interval or ratio level of measurement
- Values of the subject for the variables are normally distributed
- Student t-test, t-test, ANOVA, pearson correlation co-efficient
Non-parametric tests - Answer- - Isn't normal distribution; therefore, it is not
mathematically easily explained (Can't ever draw conclusions like cause and effect)
Measured at nominal and ordinal levels
,- Mann-whitney U test
Compare means between two distinct/independent groups - Answer- Two-sample t-test
(Parametric)
Wilcoxon ranksum test (nonparametric)
Compare two quantitative measurements taken from the same individual - Answer-
Paired t test
Wilcoxon signedrank test
Compare means between three or more distinct/independent groups - Answer- Analysis
of variance (ANOVA)
Kruskal-Wallis test
Estimate the degree of association between two quantitative variables - Answer-
Pearson coefficient of correlation
Spearman's rank correlation
Homegeneity - Answer- Type of reliability testing used with paper and pencil or scales
to address the correlation of each question to the other question within the scale ➢
Looks at the variances
➢ Collect data and the variances between the mean. Those variances around the
mean, when compared with another sample, would be similar.
➢ Should have a middle --> Some people fall above and some fall below
➢ Allows you to generalize it
Outliers - Answer- - Subjects or data points with extreme values that seem unlike the
rest of the sample
Looking for Normal Distribution Violations: - Answer- ➢ Looking at the distribution to
see if it's normal
Shape, skewness, hysteresis
Standard Deviation - Answer- Its symbol is σ
The formula is easy: it is the square root of the Variance.
Variance in this formula is - The average of the squared differences from the Mean.
Statistical Hypothesis: - Answer- statistical inference- Was the intervention being
implemented and di not happen by chance. Ex. Null, direction
One- and Two-sided hypotheses: - Answer- alternative hypothesis
Statistical significance: - Answer- results not random
Hypothesis testing: - Answer- 1. Define the research hypothesis
2. Explain how you are going to operationalize
,3. Set out the null and alternative hypothesis
4. Set the significance level.
5. Make a one- or two-tailed prediction.
6. Determine whether the distribution that you are studying is normal
7. Select an appropriate statistical test
8. Run the statistical tests
9. Reject or fail to reject the null hypothesis.
Type I error - Answer- Null hypothesis is rejected when its true
Type II error - Answer- When the null hypothesis is regarded as true but is in fact false
- often caused by flaws in the research method
Mulitvariate
Bivariate
Univariate - Answer- • Multivariate - Looking at multiple variables and trying to predict
the relationships, and maybe trying to predict if one variable effects another
• Bivariate - Comparing a bit more complex. Comparing different variable being
• Univariate - Simplest form of analysis
Regression Analysis - Answer- Used to predict the value of one variable when the value
of one or more other variables is known
- predict the value of one variable based on the value of one or more variables
- The outcome of analysis is the regression coefficient R.
- The R2 is also called the coefficient of multiple determination.
Reported as R2 = 0.63
What is probability theory? - Answer- - Deductive
- Used to explain or predict
- Expressed as p with values and percentages
Chi-Square Test of Independence - Answer- Tests for differences between expected
frequencies if groups are alike and frequencies actually observed in the data
Ex of how to report results: 2 = 4.98, df = 2, p = 0.05
Analyzing and Reporting Results
Parametric Statistical test Pearson Correlation: - Answer- Tests for the presence of a
relationship between two variables
Analyzing and Reporting Results: Explained Variances - Answer- - Regression Analysis:
The R2 is the variation between two variables expressed as a percentage.
- Cronbach's Alpha Coefficient: Tests internal consistency of measurement scale
Factor Analysis:
- Aids in development of theoretical constructs
- Aids in development of measurement scales
, Factor Analysis: two types - Answer- Confirmatory: know the dimensions
Exploratory: do not have a pre-defined idea of how many dimensions
T-Test: compares two sample means - Answer- - The "One Sample T-Test" or
"Independent Samples T-Test"-compare one group's average value to a single number
- The "paired t-test"-observations in one group is paired with a related observation in the
other group.
Performing Post Hoc Analyses - Answer- Purpose: to determine which groups are
significantly different
without which multivariate hypothesis testing would greatly suffer.
Analysis of Variance (ANOVA) - Answer- Tests for differences between means
More flexible
Multiple versions of ANOVA are available.
Reported as F = 9.75 (2, 95) (p = 0.002)
Post hoc tests are used to determine the location of differences.
Analyzing and Reporting Results: Generalizations - Answer- the application of
information that has been acquired from specific to a general
making careful inferences.
Further Research: stats - Answer- To improve the next study.
Suggestions emerge from the present study.
Strategies to further test framework in use
Conclusions and Implications - QN - Answer- It is different than the conclusion of a
paper
Conclusion is a synthesis of the findings using
Implications differ from conclusions
Judging Statistical Suitability - Answer- Factors that must be considered include:
- Study purpose
- Hypotheses, questions, or objectives
- Design
- Level of measurement
Are there dependent or independent groups?
Was performed appropriately and the results were interpreted correctly?
Was the data for analysis were treated as nominal, ordinal, or interval?
What questions are important when critically appraising statistics in a study? - Answer-
What statistics were used to describe the characteristics of the sample?
Are the data analysis procedures clearly described?
Did statistics address the purpose of the study?
Did the statistics address the objectives, questions, or hypotheses of the study?
Were the statistics appropriate for the level of measurement of each variable?
